

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCAmelCase_			      =      {
    '''configuration_squeezebert''': [
        '''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SqueezeBertConfig''',
        '''SqueezeBertOnnxConfig''',
    ],
    '''tokenization_squeezebert''': ['''SqueezeBertTokenizer'''],
}

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_			      =      ['''SqueezeBertTokenizerFast''']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_			      =      [
					    '''SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''SqueezeBertForMaskedLM''',
					    '''SqueezeBertForMultipleChoice''',
					    '''SqueezeBertForQuestionAnswering''',
					    '''SqueezeBertForSequenceClassification''',
					    '''SqueezeBertForTokenClassification''',
					    '''SqueezeBertModel''',
					    '''SqueezeBertModule''',
					    '''SqueezeBertPreTrainedModel''',
					]


if TYPE_CHECKING:
					from .configuration_squeezebert import (
					    SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    SqueezeBertConfig,
					    SqueezeBertOnnxConfig,
					)
					from .tokenization_squeezebert import SqueezeBertTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_squeezebert import (
										    SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    SqueezeBertForMaskedLM,
										    SqueezeBertForMultipleChoice,
										    SqueezeBertForQuestionAnswering,
										    SqueezeBertForSequenceClassification,
										    SqueezeBertForTokenClassification,
										    SqueezeBertModel,
										    SqueezeBertModule,
										    SqueezeBertPreTrainedModel,
										)

else:
					import sys

					lowerCAmelCase_			      =      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)







"""simple docstring"""


import itertools
import math


def        UpperCAmelCase      (					a__ ):





						'''simple docstring'''






						if 1 < number < 4:
												# 2 and 3 are primes
												return True
						elif number < 2 or number % 2 == 0 or number % 3 == 0:
												# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
												return False

						# All primes number are in format of 6k +/- 1
						for i in range(5     ,      int(math.sqrt(a__ ) + 1 )     ,      6 ):
												if number % i == 0 or number % (i + 2) == 0:
																		return False
						return True


def        UpperCAmelCase      (					):





						'''simple docstring'''






						lowerCAmelCase   :str						=			2
						while True:
												if is_prime(a__ ):
																		yield num
												num += 1


def        UpperCAmelCase      (					a__ = 1_00_01 ):





						'''simple docstring'''






						return next(itertools.islice(prime_generator()     ,      nth - 1     ,      a__ ) )


if __name__ == "__main__":
		print(F"""{solution() = }""")